Evidence map›Paper›PMID 42834372›Full record

ArticleBMC medical research methodology2026

Visual extraction of individual patient data from published kaplan-meier survival plots using a web-based application offering different reconstruction methods (V-Exploder).

Fabian Acker, Lea Ruge, Maximilian Rost, Hanna Schulte, Sophie Heinzen, Friederike C Althoff, Khouloud Kouidri, Jan Stratmann, Eva Herrmann, Martin Sebastian and 1 more

Abstract read
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Article in BMC medical research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Fabian AckerDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany. acker@med.uni-frankfurt.de.ORCID http://orcid.org/0000-0002-6207-0237
Lea RugeDepartment of Medicine 1, Hematology and Oncology, University Hospital Cologne, Cologne, Germany.
Maximilian RostDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Hanna SchulteDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Sophie HeinzenDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Friederike C AlthoffDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Khouloud KouidriDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Jan StratmannDepartment of Medicine 5, University Hospital Saarland, Pulmonology, Homburg, Germany.
Eva HerrmannInstitute for Biostatistics and Mathematical Modelling, Goethe University Frankfurt, Frankfurt, Germany.
Martin SebastianDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.
Sebastian E KoschadeDepartment of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, University Hospital, Frankfurt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividual patient-level survival data (IPD) is required for various types of medical research, such as meta-analyses and cost-effectiveness analyses. As IPD from clinical trials are usually not publicly available, secondary data utilization relies on IPD reconstruction from published Kaplan-Meier (KM) plots. In general, the established toolchains for IPD reconstruction are cumbersome and rarely offer possibilities to assess reconstruction accuracy. IMPLEMENTATION: We have therefore developed V-Exploder, an academic, non-profit, data-local tool that integrates the complete workflow of IPD reconstruction into a single browser application ( www.v-exploder.com ). Implemented methods include the iterative algorithms described by Guyot et al. and Rogula et al., and a novel, direct method for the positioning of individual events and censorings. A key feature of V-Exploder is its immediate visual feedback: recreated KM graphs are continuously constructed and superimposed onto the original figure. This enables more precise IPD reconstruction than previously possible.

methodsWe conducted a study to evaluate the IPD reconstruction performance of V-Exploder. Ten investigators each reconstructed data from four of a total of twelve figures, each showing the survival of two randomly generated cohorts (20, 50, 100, or 200 subjects in each cohort). Metrics frequently used in survival analysis were calculated for the original and reconstructed data. Median absolute errors (AE), their interquartile ranges (IQR), and root square mean errors (RMSE) are reported.

resultsSurvival metrics from reconstructed IPD showed high similarity to metrics calculated from the reference data across all datasets, investigators and used methods of IPD reconstruction. Regarding log HRs, median AE (IQR) & RMSE with the direct, Rogula, and Guyot method were 5.93 × 10

conclusionV-Exploder allows IPD reconstruction from published KM plots with high accuracy and reliability. Given its user-friendly visual interface, V-Exploder will facilitate secondary analysis of survival data and help improving analytic rigor.

Indexed as

InternetKaplan-Meier EstimateSoftwareAlgorithmsHumansCost-effectiveness analysisIndividual patient data (IPD)IPD reconstructionKaplan-Meier plotMeta-analysisSurvival analysisV-ExploderVisual extraction

Identifiers

PMID42834372
PMCPMC13640098

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.